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@article{174887,
        author = {Nikita Sarnobat and Mandar Joshi},
        title = {Enhancing Chatbot Interactions with Sentiment Analysis  Using Mistral AI and Streamlit},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2751-2755},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174887},
        abstract = {In the modern era of artificial intelligence, chatbots have become an essential part of digital communication. However, traditional chatbots lack emotional intelligence, often leading to mechanical and impersonal interactions. This research focuses on developing an AI-powered chatbot that integrates sentiment analysis to classify user messages as positive, negative, or neutral, allowing it to adjust responses dynamically. to achieve this, Streamlit is used to design an interactive UI, Mistral AI API is integrated for chatbot-like response generation, and Hugging Face is used for deployment. This paper discusses the methodology behind sentiment analysis, its implementation in chatbots, and the impact of emotional intelligence on AI interactions. The results demonstrate that chatbots with sentiment analysis provide more personalized and user-friendly interactions. Future enhancements could include multimodal sentiment analysis.},
        keywords = {Sentiment Analysis, NLP, AI, Chatbot, Mistral AI API, Streamlit, ML, Emotion Detection.},
        month = {April},
        }